A Comparison of Alternative Instruments Variables Estimators of a Dynamic Linear Model

Using a dynamic linear equation that has a conditionally homoskedastic moving average disturbance, we compare two parameterizations of a commonly used instrumental variables estimator (Hansen (1982)) to one that is asymptotically optimal in a class of estimators that includes the conventional one (Hansen (1985)). We find that for some plausible data generating processes, the optimal one is distinctly more efficient asymptotically. Simulations indicate that in samples of size typically available, asymptotic theory describes the distribution of the parameter estimates reasonably well, but that test statistics sometimes are poorly sized.

Support

The research activities of the NBER are funded by grants from federal research agencies, by private foundations, and by generous donations from our corporate associates and from private individuals. The NBER is a non-profit, 501(c)(3) organization. For information on supporting the NBER, please contact: